JMP 14.0 Online Documentation (English)
Discovering JMP
Using JMP
Basic Analysis
Essential Graphing
Profilers
Design of Experiments Guide
Fitting Linear Models
Predictive and Specialized Modeling
Multivariate Methods
Quality and Process Methods
Reliability and Survival Methods
Consumer Research
Scripting Guide
JSL Syntax Reference
JMP iPad Help
JMP Interactive HTML
Capabilities Index
JMP 13 Online Documentation
JMP 12 Online Documentation
Predictive and Specialized Modeling
• Neural Networks
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Neural Networks
Fit Nonlinear Models Using Nodes and Layers
Most features in this platform are available only in JMP Pro and noted with this icon.
The Neural platform implements a fully connected multi-layer perceptron with one or two layers. Use neural networks to predict one or more response variables using a flexible function of the input variables. Neural networks can be very good predictors when it is not necessary to describe the functional form of the response surface, or to describe the relationship between the inputs and the response.
Figure 3.1
Example of a Neural Network
Contents
Overview of the Neural Platform
Launch the Neural Platform
The Neural Launch Window
The Model Launch Control Panel
Validation Method
Hidden Layer Structure
Boosting
Fitting Options
Model Reports
Training and Validation Measures of Fit
Confusion Statistics
Model Options
Example of a Neural Network
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Help created on 7/12/2018